Google DeepMind researchers have introduced ATLAS, a set of scaling laws for multilingual language models that formalize how model size, training data volume, and language mixtures interact as the ...
Abstract: To tackle the challenge of data diversity in sentiment analysis and improve the accuracy and generalization ability of sentiment analysis, this study first cleans, denoises, and standardizes ...
A NEWLY published retrospective study has shown that AI, particularly deep-learning algorithms, can significantly reduce the rate of misdiagnosis in paediatric elbow fractures. The study analysed 755 ...
Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
Abstract: In the present work a deep learning model for the detection of diabetic retinopathy has been proposed using faster RCNN algorithm. To address the challenges in detecting abnormalities within ...
ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...
Framework Design: Designed and implemented an efficient multi-agent DRL training framework for cooperative observation scenarios. 🧠Probabilistic Estimation: Proposed a probabilistic matrix ...
A reward shaping deep deterministic policy gradient (RS-DDPG) and simultaneous localization and mapping (SLAM) path tracking algorithm is proposed to address the issues of low accuracy and poor ...
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